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Institut für Land- und Seeverkehr (ILS)Transport Systems Planning and Transport Telematics
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Order by: Author Year Journal
Grether, D. and Neumann, A. and Nagel, K. (2011). Traffic Light Control in Multi-Agent Transport Simulations.
Grether, D. S. (2014). Extension of a Multi-Agent Transport Simulation for Traffic Signal Control and Air Transport Systems. TU Berlin
Neumann, A. (2008). Modellierung und Evaluation von Lichtsignalanlagen in Queue-Simulationen. TU Berlin, Institute for Land and Sea Transport Systems
Lucas N. Alegre and Theresa Ziemke and Ana L. C. Bazzan (2020). Using reinforcement learning to control traffic signals in a real-world scenario: An approach based on linear function approximation.
José R. Correa and Tobias Harks and Kai Nagel and Britta Peis and Martin Skutella (2016). Dynamic Traffic Models in Transportation Science (Dagstuhl Seminar 15412). Dagstuhl Reports. Schloss Dagstuhl–Leibniz-Zentrum fuer Informatik, 19–34.
Nico Kühnel and Theresa Thunig and Kai Nagel (2018). Implementing an adaptive traffic signal control algorithm in an agent-based transport simulation. Procedia Computer Science. Elsevier BV, 894–899.
Thunig, T. and Kaddoura, I. and Nagel, K. (2017). Braess' paradox and congestion pricing in MATSim.
Theresa Thunig and Nico Kühnel and Kai Nagel (2019). Adaptive traffic signal control for real-world scenarios in agent-based transport simulations. Transportation Research Procedia. Elsevier BV, 481–488.
Thunig, T. and Nagel, K. (2016). Braess's paradox in an agent-based transport model. Procedia Computer Science, 946–951.
Thunig, T. and Nagel, K. (2016). Traffic optimization: Dynamic coevolutionary simulation vs. cyclically expanded networks.
Thunig, T. and Nagel, K. (2017). The structure of user equilibria: Dynamic coevolutionary simulations vs. cyclically expanded networks. Procedia Computer Science, 648–655.
Theresa Thunig and Kai Nagel (2017). Towards a robust and wide-area traffic signal control for inner-city areas. 2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS)
Thunig, T. and Nagel, K. (2019). Effects of user adaption on traffic-responsive signal control in agent-based transport simulations. 6th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), 1–7.
Theresa Thunig and Robert Scheffler and Martin Strehler and Kai Nagel (2019). Optimization and simulation of fixed-time traffic signal control in real-world applications. Procedia Computer Science. Elsevier BV, 826–833.
Theresa Ziemke and Lucas N. Alegre and Ana L. C. Bazzan (2020). A reinforcement learning approach with Fourier basis linear function approximation for traffic signal control. CEUR Workshop Proceedings, 55–62.
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